def __init__(self, site):
self.tc = client.TaskClient(('127.0.0.1', 10113))
self.rc = client.MultiEngineClient(('127.0.0.1', 10105))
self.rc.execute(fetchParse)
self.allLinks = []
self.linksWorking = {}
self.linksDone = {}
self.site = site
def main():
parser = OptionParser()
parser.set_defaults(n=100)
parser.set_defaults(tmin=1)
parser.set_defaults(tmax=60)
parser.set_defaults(controller='localhost')
parser.set_defaults(meport=10105)
parser.set_defaults(tport=10113)
parser.add_option("-n", type='int', dest='n',
help='the number of tasks to run')
parser.add_option("-t", type='float', dest='tmin',
help='the minimum task length in seconds')
parser.add_option("-T", type='float', dest='tmax',
help='the maximum task length in seconds')
parser.add_option("-c", type='string', dest='controller',
help='the address of the controller')
parser.add_option("-p", type='int', dest='meport',
help="the port on which the controller listens for the MultiEngine/RemoteController client")
parser.add_option("-P", type='int', dest='tport',
help="the port on which the controller listens for the TaskClient client")
(opts, args) = parser.parse_args()
assert opts.tmax >= opts.tmin, "tmax must not be smaller than tmin"
rc = client.MultiEngineClient((opts.controller, opts.meport))
tc = client.TaskClient((opts.controller, opts.tport))
rc.block=True
nengines = len(rc.get_ids())
rc.execute('from IPython.genutils import time')
# the jobs should take a random time within a range
times = [random.random()*(opts.tmax-opts.tmin)+opts.tmin for i in range(opts.n)]
tasks = [client.Task("time.sleep(%f)"%t) for t in times]
stime = sum(times)
print "executing %i tasks, totalling %.1f secs on %i engines"%(opts.n, stime, nengines)
time.sleep(1)
start = time.time()
taskids = [tc.run(t) for t in tasks]
tc.barrier(taskids)
stop = time.time()
ptime = stop-start
scale = stime/ptime
print "executed %.1f secs in %.1f secs"%(stime, ptime)
print "%.3fx parallel performance on %i engines"%(scale, nengines)
print "%.1f%% of theoretical max"%(100*scale/nengines)
#!/usr/bin/env python
# encoding: utf-8
"""Run a Monte-Carlo options pricer in parallel."""
from ipython1.kernel import client
import numpy as N
from mcpricer import MCOptionPricer
tc = client.TaskClient(('127.0.0.1', 10113))
rc = client.MultiEngineClient(('127.0.0.1', 10105))
# Initialize the common code on the engines
rc.run('mcpricer.py')
# Push the variables that won't change (stock print, interest rate, days and MC paths)
rc.push(dict(S=100.0, r=0.05, days=260, paths=10000))
task_string = """\
op = MCOptionPricer(S,K,sigma,r,days,paths)
op.run()
vp, ap, vc, ac = op.vanilla_put, op.asian_put, op.vanilla_call, op.asian_call
"""
# Create arrays of strike prices and volatilities
K_vals = N.arange(90.0, 110.0, 2.0)
sigma_vals = N.arange(0.02, 0.3, 0.02)
# Submit tasks
taskids = []
for K in K_vals:
for sigma in sigma_vals: